{"id":"W4323035284","doi":"10.1002/9781119790686.ch33","title":"AI for Workflow Enhancement in Radiology","year":2023,"lang":"en","type":"other","venue":"AI in Clinical Medicine","topic":"Radiology practices and education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; McMaster University; Vancouver General Hospital","funders":"","keywords":"Workflow; Radiology; Computer science; Workflow technology; Scheduling (production processes); Medical physics; Medicine; Engineering; Database; Operations management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002486629,0.0002278663,0.001277984,0.0004446706,0.00001219562,0.000002010684,0.0001401267,0.0009177278,0.001633483],"category_scores_gemma":[0.005777772,0.0001727302,0.0001081909,0.0003017406,0.0003076287,0.00002354537,0.00002498502,0.001080233,0.0001964525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001112306,"about_ca_system_score_gemma":0.0002069883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00046881,"about_ca_topic_score_gemma":0.00134512,"domain_scores_codex":[0.9975247,0.000188736,0.001168725,0.0005813141,0.0001489538,0.0003875194],"domain_scores_gemma":[0.9959708,0.003048834,0.0003313407,0.0004601819,0.0000390491,0.0001498364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003700956,0.0002688878,0.02709875,0.0001571872,0.0001049017,0.0000595983,0.0000791755,6.916214e-7,0.000005251466,0.0001608003,0.9045091,0.06718557],"study_design_scores_gemma":[0.005106235,0.001785974,0.03184934,0.002258048,0.0001640428,0.00002088847,0.00007039824,0.0001426272,9.183926e-7,0.0007553196,0.9576939,0.000152305],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.003865351,0.01971406,0.001593885,0.6988875,0.03782232,0.006677911,0.00001785037,0.0005525738,0.2308686],"genre_scores_gemma":[0.008004473,0.05576558,0.002738511,0.0861985,0.02092421,0.001006366,0.0004366529,0.00113029,0.8237954],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.612689,"threshold_uncertainty_score":0.9992791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1261507101423596,"score_gpt":0.5189640611812709,"score_spread":0.3928133510389114,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}